Role of ferroptosis-related genes in periodontitis based on integrated bioinformatics analysis

Background Cell survival or death is one of the key scientific issues of inflammatory response. To regulate cell death during the occurrence and development of periodontitis, various forms of programmed cell death, such as pyroptosis, ferroptosis, necroptosis, and apoptosis, have been proposed. It has been found that ferroptosis characterized by iron-dependent lipid peroxidation is involved in cancer, degenerative brain diseases and inflammatory diseases. Furthermore, NCOA4 is considered one of ferroptosis-related genes (FRGs) contributing to butyrate-induced cell death in the periodontitis. This research aims to analyze the expression of FRGs in periodontitis tissues and to explore the relationship between ferroptosis and periodontitis. Method Genes associated with periodontitis were retrieved from two Gene Expression Omnibus datasets. Then, we normalized microarray data and removed the batch effect using the R software. We used R to convert the mRNA expression data and collected the expression of FRGs. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), transcription factor (TF) and protein-protein interaction (PPI) network analyses were used. In addition, we constructed a receiver operating characteristic curve and obtained relative mRNA expression verified by quantitative reverse-transcription polymerase chain reaction (PCR). Results Eight and 10 FRGs related to periodontitis were upregulated and downregulated, respectively. GO analysis showed that FRGs were enriched in the regulation of glutathione biosynthetic, glutamate homeostasis, and endoplasmic reticulum-nucleus signaling pathway. The top TFs included CEBPB, JUND, ATF2. Based on the PPI network analysis, FRGs were mainly linked to the negative regulation of IRE1-mediated unfolded protein response, regulation of type IIa hypersensitivity, and regulation of apoptotic cell clearance. The expression levels of NCOA4, SLC1A5 and HSPB1 using PCR were significantly different between normal gingival samples and periodontitis samples. Furthermore, the diagnostic value of FRGs for periodontitis were “Good”. Conclusions We found significant associations between FRGs and periodontitis. The present study not only provides a new possible pathomechanism for the occurrence of periodontitis but also offers a new direction for the diagnosis and treatment of periodontitis.


Introduction
Periodontitis is characterized by pathological loss of the periodontal ligament and alveolar bone. It is affected by multiple actions of herpes viruses, bacterial pathogens and immune responses [1]. Tissue destruction in periodontitis is considered to be due to an excessive inflammatory response to bacterial plaque. When protecting the host from microbial invasion, polymorphonuclear neutrophils can cause an upregulated response of reactive oxygen species (ROS) [2][3][4][5]. ROS plays a key role in periodontitis due to excessive lipid peroxidation and tissue damage [6,7].
Ferroptosis is a form of cell death that depends on iron regulation; it is caused by the accumulation of active oxygen in lipids and loss of activity of the lipid repair enzyme GPX4 [8]. Furthermore, ferroptosis has different molecular characteristics from other forms of cell death [9]. There are two main pathways of ferroptosis, the transporter-dependent pathway and the enzyme-regulated pathway [10]. Data from several studies suggest that the biochemical hallmarks of ferroptosis include accumulation of cellular iron, induction of lipid peroxidation, and loss of antioxidant defense [11]. Ferroptosis has been associated with various pathological conditions such as tumor [12], degenerative diseases [13], ischemia-reperfusion injury [14], and inflammatory diseases [15]. Previous studies have determined that 24 genes play a key role in regulating ferroptosis [16]. These genes are defined as ferroptosis-related genes (FRGs) [17]. In general, the main ferroptosis-inducing event is lipid peroxidation. Interestingly, the characteristics of periodontitis include increased metabolites of lipid peroxidation, alveolar bone resorption, and increased inflammatory factors [18]. However, whether the periodontal pathogens can induce ferroptosis has rarely been reported.
Based on the results of previous studies [19,20], we designed the present study to analyze the effects of ferroptosis on periodontitis using bioinformatics methods and found that there is a clear association between ferroptosis and periodontitis.

Microarray data
Two microarray datasets of Periodontitis-GSE16134 and GSE10334-were downloaded from the GEO database (http://www.ncbi.nlm.nih.gov/geo/), using the following keywords: "periodontitis," and "Homo sapiens." GSE16134 and GSE10334 were submitted by Demmer RT, Pavlidis P, Papapanou PN. Since these were public datasets, it is impossible to obtain comprehensive personal information, which appears to be a potential limitation. The data obtained from GEO is shown in Table 1.

Normalized data and batch effect removed
The normalization of data was realized by log2 transformation. PreprocessCore package (R version: 3.4.1) was used to normalize the microarray data. Then we converted the probes into gene symbols according to the GEO annotation information. The probes containing multiple genes were integrated by averaging. Variance stabilized counts was used to control initial quality and individual horse effect removed by the Remove Batch Effect function of limma R package.

Enrichment analyses
The ferroptosis-related genes were uploaded to the ClueGo (version: 2.5.7). P <0.05 indicates a significant difference. In order to confirm the underlying function, the differentially expressed genes (DEGs) were analyzed through GO functional enrichment. GO is a representative and standardized work platform for terminology description or word meaning interpretation of gene and gene product characteristics. The role of FRGs in healthy tissues was observed by Metascape (https://metascape.org). We used the Cluster Profiler package (R version: 4.0.3) to analyze the GO function of DEGs. KEGG is known for "understanding the advanced functions of biological systems and a library of utility programs". KOBAS 3.0 (http:// kobas.cbi.pku.edu.cn/kobas3) was used to enrich the KEGG pathway [21]. The box plot was implemented by the ggplot2 package; PCA graphs were drawn by the ggord package; the heat map was displayed by the pheatmap package.

ChIP-X enrichment analysis 3 (ChEA3)
ChEA3 (https://amp.pharm.mssm.edu/ChEA3) is a tool to find TF targets and sort them [22]. We can use it to obtain related biological functions of FRGs.

PPI network construction and module analysis
We used the STRING (version: 11.0) (http://string-db.org) to construct a PPI network of the FRGs and the DEGs. When the composite score is> 0.4, the interaction is significant. More in-depth analysis of the interactive network can be realised by the Cytoscape (version: 3.8.2).

Real-time quantitative PCR (qRT-PCR)
RNA was extracted from gingival samples using RNAiso Plus (TaKaRa, China). Then we used cDNA synthesis kit (TIANGEN, China) to reverse transcription. The primers for qRT-PCR were supply by GENERAL BIOL (China). The comparative 2 −ΔΔCt method was used for relative quantification. The primer sequences were described by Table 2. The analysis were calculated using GraphPad (version: 8.0.1). Statistical significance between two groups was evaluated by t test (p < 0.05).

Identification of up/downregulated DEGs and FRGs
128 common DEGs in GSE16134 and GSE10334 between affected and unaffected groups were identified using R. We found that 101 DEGs were significantly upregulated and 27 DEGs were significantly downregulated (Table 3)

GO enrichment
GO (Fig 4) showed that upregulated DEGs were enriched for humoral immune response, response to molecule of bacterial origin, extracellular structure organization, phagocytosis, and leukocyte cell-cell adhesion. Downregulated DEGs were enriched for the epidermis development, skin development, keratinocyte differentiation, keratinization, and epidermal cell differentiation. The results of functional enrichment analysis of FRGs in normal tissues are shown in S1 Table.

GO-Biological process of ferroptosis-related genes
It was found that overlapping targets of ferroptosis-related genes in periodontitis were involved in 34 pathways by using ClueGO analysis, including regulation of glutathione biosynthetic, glutamate homeostasis, ER-nucleus signaling pathway, response to gamma radiation, protein folding chaperone, positive regulation of B cell proliferation, protein serine/threonine kinase inhibitor activity, and so on (Fig 6).

TF target analysis
The TFs were found to be distributed in various tissues, such as the muscle, brain, testis, and blood ( Fig 7A). And the TF targets' functions included immune response, DNA transcription, and skeletal muscle tissue development (Fig 7B). The top 10 TFs included CEBPB, JUND, ATF2, CEBPD, and JUN (Fig 7C).

PPI analysis
We used the Cytoscape and STRING databases to determin the greatest degree of network connection. The top ten hub genes identified were CXCL8, CXCR4, IL1B, CD19, SELL, CXCL1, CXCL12, CSF3, PECAM1, FCGR2B. And theTOP3 hub nodes connected to FRGs were CXCL8, FOS, ATP5G3. These genes were mainly linked to the negative regulation of IRE1-mediated unfolded protein response, regulation of type IIa hypersensitivity, regulation of apoptotic cell clearance, CXCR chemokine receptor binding, IgG binding, structural constituent of epidermis (Fig 8).

qRT-PCR experiment
To further confirm the bioinformatics analysis results, 6 normal gingival samples and 6 diseased samples were collected. Fig 10 shows the expression levels of NCOA4, SLC1A5 and HSPB1 were significantly changed between normal gingival samples and diseased samples (p < 0.05).

Discussion
Currently, various factors, including smoking, alcohol, metabolic syndrome, and obesity, were deemed to be the contributing factors of periodontitis [23]. However, understanding of the pathogenesis of the disease is still limited. Based on the RNA-seq, Davanian H confirmed that the elevated levels of locally produced cytokines in the periodontium [24]. A recent study including molecular biology experiments showed that NCOA4, one of the FRGs, is related to the occurrence and development of periodontitis, indicating that iron homeostasis plays an important role in the pathogenesis of periodontitis [20]. Ferroptosis triggers excess intracellular ROS and promotes lipid peroxidation, which is critical for inflammation. This study aimed to identify FRGs associated with periodontitis using bioinformatics analysis and may provide a deeper understanding of the link between ferroptosis and periodontitis. Also, this study has a potential value for the diagnosis, prognosis, and treatment of periodontitis. We analyzed two mRNA microarray datasets, obtained differentially expressed genes (DEGs), and screened FRGs from affected and unaffected group. A total of 128 DEGs and 18 screened FRGs were identified between the two datasets. Then, the DEGs and screened FRGs were subjected to GO and KEGG pathway analysis. PPI analysis of DEG and FRG was performed to enhance our understanding of the molecular mechanisms between periodontitis and ferroptosis, revealing a strong association between FRG and DEG at the protein level. To confirm the validity of these results, we conducted polymerase chain reaction (PCR) analysis for molecular biological verification at the gene level and ROC analysis to further understand the relationship between FRG and DEG. We analyzed the pathway and functional enrichment of screened FRGs between the two groups as well as the results including glutathione biosynthetic. Some studies confirm that glutathione levels in patients with periodontitis are higher than those in healthy individuals, which is related to oxidative stress [25]. ROS regulates NF-κB responses, and one of the major signaling pathways that intersect with NF-κB in terms of ROS and cell death is the crosstalk that occurs between NF-κB and JNK [26]. According to various studies, glutathioneization regulates the activity of many transcription factors (TFs) through the binding of glutathione to the DNA-binding domain, which contains the TF NF-κB. Moreover, NF-κB plays an important role in the activation of pro-inflammatory responses [27,28].   The GO analysis results revealed that the upregulated DEGs were enriched in the humoral immune response, response to molecule of bacterial origin, and extracellular structure organization, whereas the downregulated DEGs were enriched in epidermis development, skin development, and keratinocyte differentiation. More and more evidence shows that cells dying by ferroptosis secrete factors that activate the immune system as expressed in the vivo pathological and genetic models of ferroptosis [29]. This can cause a periodontal immune response and reduce gingival development, clarifying the clinical manifestations of periodontitis. The KEGG pathway analysis indicated that the regulated DEGs were mainly enriched in chemokine signaling pathway [30,31]. In addition, we established a DEG and screened FRG PPI network, the hub genes include chemokines such as CXCL8, CXCR4, CXCL1 and CXCL12. And theTOP3 hub nodes connected to screened FRG were CXCL8, FOS, ATP5G3. Some studies have shown that chemokines are small proteins that secreted by cells that influence the

PLOS ONE
immune system. CXCL8 (interleukin-8) is a cytokine in the chemokine family [32] and an activator of neutrophils in inflammatory areas, which is released by gingival fibroblasts [33]. The final regulation of CXCL8 gene expression depends on the ratio of CEBPB to NF-κB [34]. CEBPB is an important TF regulating the expression of immune and inflammatory responserelated genes. Interestingly, CEBPB is one of the TF targets of FRGs in our study. We believe that CEBPB also plays an important role in periodontitis-related immune responses [35][36][37]. Meanwhile, researchers have found that ATF2 is related to the occurrence of aggressive periodontitis [29]. These results suggest that TF targets and their signaling pathway genes are drivers of periodontitis progression. We also found that the analysis results of the downregulated genes include NCOA4, which is important in periodontitis. An article pointed out that periodontitis is mostly correlated with NCOA4-mediated ferritinophagy in intracellular iron level regulation [20], p38/hypoxia inducible factor-1α pathway activation, and bromodomain-containing protein 4 and cyclin-dependent kinase 9 transcription modulation mediated butyratetriggered NCOA4 expression in periodontal ligament fibroblasts [19]. Conversely, NCOA4 over-expression increased sensitivity to ferroptosis [38]. It is fascinating that our biological experiments have proved that NCOA4 is increased, and it also reminds us that transcriptomic datasets have certain drawbacks [39]. The difference in results is also because periodontitis is a disease affected by multiple factors [40]. We still need to further study the relationship between ferroptosis and periodontitis in the future. Through the comprehensive analysis of bioinformatic results, we speculated that ferroptosis promoted the occurrence and development of periodontitis through oxidative stress ROS and NF-κB related pathways.
The bioinformatic analysis of this study was based on published data and quantitative reverse-transcription PCR analysis with a relatively small number of samples to explore the relationship between FRGs and periodontitis. Further studies on the prediction and validation of periodontitis treatment targets including more samples and more forms of molecular biology validation are required.

Conclusion
In summary, the present study determined the effect of ferroptosis in periodontitis. Ferroptosis provides new insights for understanding and preventing periodontitis. Better understanding of ferroptosis in periodontitis may aid in the diagnosis and treatment of periodontitis. Due to